Description

You will design and implement machine learning models and data ingestion pipelines within hybrid and multi-cloud environments. You will build and maintain data pipeline architecture by assembling large, complex data sets. You will develop and support a platform for data scientists to develop, train, and experiment with models. You will expand and optimize data pipelines, data flow, and collection for cross-functional teams. You will implement machine learning and big data platforms specifically using AWS SageMaker.

Responsibilities

• Design and implement machine learning models and data ingestion pipelines.
• Build and maintain data pipeline architecture using large, complex data sets.
• Develop and support a platform for data scientists to develop, train, and experiment with models.
• Expand and optimize data pipelines, data flow, and collection for cross-functional teams.
• Implement machine learning and big data platforms specifically using AWS SageMaker.

Required Skills

• At least 2 years of experience as a machine learning engineer.
• Advanced proficiency in Python, Java, and Scala.
• Strong computer science fundamentals in algorithms, data structures, and multithreading.
• Experience with object-oriented development, distributed applications, and client-server architecture.
• Knowledge of client frameworks, libraries, data modeling, and software architecture.
• Solid understanding of mathematics, statistics, and algorithms.
• Bachelor's degree in computer science, data science, mathematics, or a related field.

Preferred Skills

• Master's degree in a related field.
• Experience with container, streaming, and messaging technologies.

Key Skills

Education

Bachelor's degree